image_sort_by_statistics.h

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/***************************************************************************
 * Authors:     Carlos Oscar Sorzano (coss@cnb.csic.es)
 *              Javier Vargas (jvargas@cnb.csic.es)
 *
 * Unidad de  Bioinformatica of Centro Nacional de Biotecnologia , CSIC
 *
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 2 of the License, or
 * (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program; if not, write to the Free Software
 * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA
 * 02111-1307  USA
 *
 *  All comments concerning this program package may be sent to the
 *  e-mail address 'xmipp@cnb.csic.es'
 ***************************************************************************/

#ifndef _PROG_IMAGE_SORT
#define _PROG_IMAGE_SORT

#include "core/xmipp_program.h"
#include "core/xmipp_filename.h"
#include "core/metadata_vec.h"
#include "data/basic_pca.h"

class ProgSortByStatistics: public XmippProgram
{
public:
    FileName fn, fn_out, fn_train;
    bool addToInput, addFeatures;
    int targetXdim;

public:
    double cutoff, per;

    std::vector<PCAMahalanobisAnalyzer> pcaAnalyzer;
    MetaDataVec SF, SFtrain;

public:
    void clear();

    void readParams();

    void defineParams();

    //Method to obtain a zScore of each extracted particle. The process is based on a segmentation approach using
    //the Spiral Phase Transform (SPT), then the respective binary image is fitted to an ellipse and we obtain the major
    //and minor axis. Also a other coarser descriptor based on the image histogram is used to detect outliers. Additionally,
    //the centroid of the normalized image (SPT) is used as a descriptor but with a very low weight in the zScore
    //JavierVargas : September 2012 BCU
    void processInputPrepareSPTH(MetaData &SF, bool trained);

    void run();
};
#endif